3. Electronic Theses and Dissertations (ETDs) - All submissions
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Item Evaluating efficiency of ensemble classifiers in predicting the JSE all-share index attitude(2017) Ramsumar, ShaunThe prediction of stock price and index level in a financial market is an interesting but highly complex and intricate topic. Advancements in prediction models leading to even a slight increase in performance can be very profitable. The number of studies investigating models in predicting actual levels of stocks and indices however, far exceed those predicting the direction of stocks and indices. This study evaluates the performance of ensemble prediction models in predicting the daily direction of the JSE All-Share index. The ensemble prediction models are benchmarked against three common prediction models in the domain of financial data prediction namely, support vector machines, logistic regression and k-nearest neighbour. The results indicate that the Boosted algorithm of the ensemble prediction model is able to predict the index direction the best, followed by k-nearest neighbour, logistic regression and support vector machines respectively. The study suggests that ensemble models be considered in all stock price and index prediction applications.Item Interaction between macroeconomic fundamentals and energy prices: evidence from South Africa(2017) Diale, Tumelo KGrowth in commodity exporting economies, such as South Africa, is highly dependent on the revenue generated from exports. It is thus evident that as commodity prices fluctuate, income and the balance of payments will be accordingly impacted. This is further exacerbated by strong dependence on the imports of certain commodities. Oil is one such commodity on whose imports South Africa is highly dependent. Although natural gas is also imported, it is in lower quantities and is as such expected to impact South Africa to a lower extent. Coal, on the other hand, is among the main commodity exports and was expected to have an impact on (and be impacted by) South African macroeconomic fundamentals. In this study, we use a VECM and MGARCH model to test the interaction between South African macroeconomic variables and these three commodities. Our VECM findings indicate that oil and exchange rates are inflationary. This implies that an increase in oil prices and/or exchange rates (indicating a depreciation of the Rand against the U.S. Dollar) results in an increase in inflation. Inflation, on the other hand, propagates higher coal prices and to a lesser extent, higher interest rates. We account the latter to South Africa’s inflation targeting regime and the former to demand and supply dynamics which occur at RBCT as production costs increase (short-term coal export contracts and spot market sales). Natural gas is found to have weak impacts on interest rates and exchange rates. Our MGARCH model shows that only the innovations in natural gas and oil prices spillover into interest rates and exchange rate. There is no direct spillover captured. However, there is strong direct spillover from oil to inflation. Lastly, interest rates are found to have a strong direct volatility spillover to both oil and natural gas. We attribute this to the exchange rate impact that interest rates have and is supported by the exchange rate impact on commodity price volatility. We conclude that an in-depth understanding of triggers is pertinent for monetary and fiscal policy decisions in South Africa. Although the South African economy is relatively diversified compared to other developing countries, commodity price fluctuations do have a significant impact on economic performance.Item Does the Taylor Rule outperform market forecasts of interest rates?(2016) Msipa, ChipoThis study sets out to investigate whether the Taylor Rule provides better the forecasts of the future short-term interest rates than the yield curve in the South African market. For the Taylor Rule we use OLS and use the open-market forward-looking Taylor Rule to forecast interest rates. For the yield curve, simple linear interpolation is used to derive forecast. We find that in the short term, forecasted one-month ahead interest rates closely track the actuals interest rates for both models. At longer horizons, there are larger deviations of forecasts from the actual. The RMSE analyses support the Taylor Rule as a superior forecasting model in all forecasting horizons.